Evidence map›Paper›PMID 37237309›Full record

ArticleBMC public health2023

Association of depressive symptoms with retirement in Chinese employees: evidence from national longitudinal surveys from 2011 to 2018.

Fenglin Xu, Jingmin Yuan, Hongxia Wu

Open access · goldAbstract read
In one paragraph

Article in BMC public health, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
7.8field-weighted citation impact, top 3% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Article
  2. Article
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  4. Article
  5. Depressive symptoms and receipt of pensions: a cross-sectional analysis of the ELSI-Brazil study.Epidemiologia e servicos de saude : revista do Sistema Unico de Saude do Brasil · 2023
    Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

3 authors at 3 institutions in 1 country.

Fenglin XuDepartment of Nursing, Hubei College of Chinese Medicine, Jingzhou, China.
Jingmin YuanHealth Science Center, Yangtze University, Jingzhou, China. yuanjingmin@yangtzeu.edu.cn.
Hongxia WuDepartment of Respiratory and Critical Care Medicine, Shanxi Provincial People's Hospital, Taiyuan, China. sanyafangd@163.com.
Hubei University of Chinese Medicine · CNShanxi Medical University · CNYangtze University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundThe relationship between depressive symptoms and retirement remains controversial. Thus, we aimed to explore the effect of retirement on individuals' depressive symptoms in Chinese employees.

methodsIn this panel data analysis, a data set from China Health and Retirement Longitudinal Study (CHARLS) in 2011, 2013, 2015 and 2018 was adopted with a total of 1390 employees aged ≥ 45-years-old who had complete follow-up for the four waves. Random-effects logistic regression was used to examine the associations between retirement and depressive symptoms.

resultsAfter adjusting several socio-demographic variables, retirement still increases the risk of depressive symptoms in the retirees (odds ratio 1.5, 95% CI 1.14-1.97). Through subgroup analysis, we found that people who are male, with lower education level, married, living in rural areas, suffering from chronic diseases, and those who do not participate in social activities are more likely to experience depression after retirement.

conclusionsRetirement can increase the depression risk of Chinese employees. It is necessary to formulate relevant supporting policies to reduce the risk of depression.

Indexed as

DepressionRetirementChinaChronic DiseaseEast Asian PeopleFemaleHumansLongitudinal StudiesMaleMiddle AgedCHARLSChina, Older adultsDepressive symptomRetirement

Identifiers

PMID37237309
PMCPMC10214712
OpenAlexW4378384286

What OpenQuestion holds

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LicenceCC BY
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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.